A fast self-adaptive differential evolution algorithm(FSADE) for the complex nonlinear power economic load
dispatch problem is proposed. In the view of vector operation, the mutant operator of basic differential evolution algorithm
is analyzed, then an improved mutant operator is proposed to improve the convergence speed greatly. According to the
individual evolutionary process, a self-learning mechanism is introduced to adapt the mutation constant and crossover
probability constant. As a result, the robustness of the proposed algorithm is improved. To demonstrate the effectiveness
of the proposed algorithm, three classical test cases are conducted and compared with four other intelligent optimization
algorithms. The experiment results show that the proposed FSADE is an very effective algorithm for solving the power
economic dispatch.